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# Created by Keivalya Pandya
# using https://huggingface.co/docs/api-inference/tasks/chat-completion
import gradio as gr
from huggingface_hub import InferenceClient
"""
For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
"""
client = InferenceClient("microsoft/Phi-3-mini-4k-instruct")
# client = InferenceClient("meta-llama/Llama-3.1-8B-Instruct")
# def yodaify_text(text):
# """
# Convert the assistant's response to Yoda-style speech.
# """
# words = text.split()
# if len(words) > 4:
# return f"{' '.join(words[2:])}, {words[0]} {words[1]}"
# return f"{' '.join(words[::-1])}"
def respond(
message,
history: list[tuple[str, str]],
# system_message,
# max_tokens,
# temperature,
# top_p,
):
messages = [{"role": "assistant", "content": "You are a helpful assistant who always talks like Yoda from Star Wars."}]
for val in history:
if val[0]:
messages.append({"role": "user", "content": val[0]})
if val[1]:
messages.append({"role": "assistant", "content": val[1]})
messages.append({"role": "user", "content": message})
response = ""
for message in client.chat_completion(
messages,
max_tokens=128,
stream=True,
temperature=0.3,
top_p=0.8,
):
token = message.choices[0].delta.content
response += token
# Modify assistant response to Yoda-style speech
# yoda_response = yodaify_text(response)
# yield yoda_response
yield response
"""
For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
"""
demo = gr.ChatInterface(
respond,
# additional_inputs=[
# gr.Textbox(value="You are Yoda from Star Wars.", label="System message"),
# gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
# gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
# gr.Slider(
# minimum=0.1,
# maximum=1.0,
# value=0.95,
# step=0.05,
# label="Top-p (nucleus sampling)",
# ),
# ],
)
if __name__ == "__main__":
demo.launch()
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